class_docstr: Clusterer Ensemble combines multiple base clustering estimators by
  alignment. See :cite:`zhou2006clusterer` for details.
  
  Parameters
  ----------
  base_estimators : list or numpy array of shape (n_estimators,)
      A list of base estimators. Estimators must have a `labels_`
      attribute once fitted. Sklearn clustering estimators are recommended.
  
  n_clusters : int, optional (default=8)
      The number of clusters.
  
  weights : numpy array of shape (n_estimators,)
      Estimator weights. May be used after the alignment.
  
  reference_idx : int in range [0, n_estimators-1], optional (default=0)
      The ith base estimator used as the reference for label alignment.
  
  pre_fitted : bool, optional (default=False)
      Whether the base estimators are trained. If True, `fit`
      process may be skipped.
  
  Attributes
  ----------
  labels_ : int
      The predicted label of the fitted data.
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docstr: Predict the class labels for the provided data.
  
  Parameters
  ----------
  X : numpy array of shape (n_samples, n_features)
      The input samples.
  
  Returns
  -------
  labels : numpy array of shape (n_samples,)
      Class labels for each data sample.
docstr_tok: ["Predict","the","class","labels","for","the","provided","data",".","Parameters","--","--","--","--","--","X",":","numpy","array","of","shape","(","n_samples",",","n_features",")","The","input","samples",".","Returns","--","--","--","-","labels",":","numpy","array","of","shape","(","n_samples",",",")","Class","labels","for","each","data","sample","."]
code: def predict_proba(self, X):
      """Predict the class labels for the provided data.
  
      Parameters
      ----------
      X : numpy array of shape (n_samples, n_features)
          The input samples.
  
      Returns
      -------
      labels : numpy array of shape (n_samples,)
          Class labels for each data sample.
      """
      raise NotImplemented(
          "predict_proba function is currently disabled for"
          "clustering due to inconsistent behaviours."
      )
  
file_path: combo/combo/models/cluster_comb.py
imports: import numpy
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from numpy.testing import assert_equal
  from pyod.utils.utility import check_parameter
  from .base import BaseAggregator
  from .score_comb import majority_vote
label_desc: Use image node_id 4 for calling the ClustererEnsemble obj's underlying member method code with example usage: obj.predict_proba(X) without return types